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I have a Windows-based desktop application that already speaks, but I want it to sound unmistakably natural in Español Castellano and allow users to switch to this new custom voice on demand. Your task is to fine-tune an existing neural text-to-speech model so it delivers that polished Castilian tone, then package it so my app can call it locally without relying on any cloud service. You’re free to work with the toolkit you know best—Tacotron-2, FastSpeech-2, Glow-TTS, VITS, or a comparable neural approach—as long as the final runtime is lightweight, runs offline on Windows 10/11, and exposes a simple DLL or command-line interface my app can invoke. Deliverables • Fine-tuned Castilian Spanish voice model files • Windows-ready inference runtime (ONNX...

I have a collection of CT scans and I need to learn, step by step, how to isolate the complete vascular tree from each volume. My end goal is to be able to run the full workflow on my own, so I’m looking for an experienced medical-image segmentation specialist who can mentor me through best practices and common pitfalls rather than simply handing over a finished model. During our sessions I’d like to cover everything from data preparation and augmentation, through model selection and training, to post-processing and quantitative evaluation. I have my own PACS system and studies (research lab) and have 3D slicer, ITK-SNAP and sim-vascular. Deliverables I expect at the end of the engagement: • A reproducible segmentation pipeline that I can apply to various organs from C...

want the exact facial-expression editor from the video running on a GPU server in Docker, exposed via a simple API that takes image + slider values and returns the edited image. Reply with your description and complete understanding of the project. If you have not watched the video do not apply!

The project centers on building a production-ready TensorFlow 2.x model that classifies tabular data delivered to us through an internal API. I have the API specifications and sample payloads ready; you will turn those streams into a clean training pipeline, engineer the right features, and iterate until the classifier meets our performance targets in real-world tests. Scope of work • Data pipeline – pull the API data, handle preprocessing, and produce TensorFlow-friendly datasets for train/val/test splits. • Model development – design, train, and tune a deep learning architecture suitable for tabular inputs (e.g., wide & deep, Transformer, or other proven structures). • Optimization – experiment with hyperparameters, regularization, and callback...

I will provide Photos and Videos with different quality and format of a certain person. All data provided should be organized (useable for training or not) and processed (extract frames from Videos, if needed) to train an AI model for use with Stable Diffusion (ComfyUI) to create Photos and Videos of that person. The content created through the AI model should be: - As realistic as possible - As consistent as possible to create the Character trained with - Create high quality content - Uncensored All Data provided and created is confidential. It is prohibited to share any data, use it in any different way than fulfilling the purpose described above and has to be completely deleted as soon as the project is finished.

Project Description: I am looking for an experienced Deep Learning / Machine Learning professional to complete a full academic-style project. I will provide: Dataset (train, validation, test images) Example baseline code (starter CNN + DenseNet example) Assignment brief and marking criteria Your job is to complete the full project to a high standard. Component 1 — Coursework (70%) Task: Build and compare two models for Cardiomegaly detection in chest X-ray images: Baseline CNN (custom architecture) DenseNet121 (transfer learning) What I Will Give You: Full dataset (224×224 images) Starter code (both models) Example paper / similar study Your Responsibilities: Model Development Train/validate/test both models Tune hyperparameters Solve issues (overfitting, imbalan...

I want a Python-based workflow that starts with gathering historical stock prices and ends with a working deep-learning model that can generate forward-looking signals. The data should come from Prowess CMIE, NSE/BSE feeds, and—where gaps exist—Yahoo Finance. Once collected, the prices must be cleaned, merged, and stored in a reproducible format (CSV or a lightweight database is fine). After the data pipeline is in place, I’d like you to design and train a predictive model—preferably a deep neural network—using well-known libraries such as pandas, NumPy, scikit-learn, and either TensorFlow or PyTorch. The emphasis is on producing an end-to-end, repeatable process that I can run locally to refresh the dataset and retrain the model. Deliverables • Pytho...

The project centers on building a production-ready TensorFlow 2.x model that classifies tabular data delivered to us through an internal API. I have the API specifications and sample payloads ready; you will turn those streams into a clean training pipeline, engineer the right features, and iterate until the classifier meets our performance targets in real-world tests. Scope of work • Data pipeline – pull the API data, handle preprocessing, and produce TensorFlow-friendly datasets for train/val/test splits. • Model development – design, train, and tune a deep learning architecture suitable for tabular inputs (e.g., wide & deep, Transformer, or other proven structures). • Optimization – experiment with hyperparameters, regularization, and callback...

I need a complete camera solution that can sit on a fixed pole beside a 6-a-side turf and automatically keep the football centred in the frame at all times. I am counting on image-recognition tracking, not GPS or external sensors, to find the ball and drive a pair of smooth, low-latency servos that pan and tilt the lens. The system must offer both live streaming for spectators and coaches and simultaneous high-quality recording for later analysis. A single operator-free setup is the goal: once the match starts, the camera should lock on, follow play end-to-end, and store the full session without further input. Key deliverables • Hardware specification and wiring diagram, including recommended servos, camera module, processing unit (e.g., Jetson, Raspberry Pi + accelerator, or si...

I need a lightweight AI model that can flag deepfakes in both still photos and the individual frames of a video. The goal is moderate, reliable accuracy—good enough to separate obvious fakes from genuine content without the heavy-duty infrastructure a research-grade solution would demand. I just want clean, well-commented code that someone with basic ML/DL familiarity can pick up and run on a CPU. Deliverables • Trained model file and all training scripts • Inference script or notebook that accepts an image or video file and returns a deepfake probability score plus a simple real/fake label • Brief README explaining setup, model architecture, and how to retrain or fine-tune on new data • A short report (a page or two) summarizing achieved accuracy, datas...

I need an end-to-end Natural Language Processing solution that can take raw text and return intelligent, context-aware results. The exact task set is still flexible, but the core requirement is that the model handles free-form language reliably; whether that means generating coherent replies, classifying sentiment, or extracting entities will depend on what you advise after a quick technical discovery call. Here is what I expect to walk away with: • A trained NLP model (Python, PyTorch or TensorFlow preferred) wrapped in clean, well-documented code. • A lightweight REST or GraphQL API so the model can be plugged straight into my front-end of choice—web, mobile, or desktop. • Clear setup instructions and a short walkthrough video or live demo confirming everythin...

I need a visual-transformer–based pipeline that can take raw EEG recordings and structural MRI scans, fuse the two modalities, and output a clear diagnostic decision for psychiatric disorders. The end goal is a medical-grade tool that helps clinicians distinguish between healthy controls and patients, so accuracy and interpretability matter more to me than sheer benchmark speed. Here is what I already have and what I expect from you: • Well-curated datasets of synchronized EEG and MRI are available under research licences; I will provide access links once the project starts. • You will design or adapt a Vision Transformer (ViT) backbone, convert the EEG into image-like representations (e.g., time–frequency spectrograms or topographic maps) and merge them with MRI ...

I am seeking a highly qualified Academic Researcher with a proven publication record to author a high-level research "full" paper targeting SCI (Science Citation Index) or SSCI (Social Sciences Citation Index) journals. The topic must be within the domain of Management Information Systems (MIS), specifically focusing on Artificial Intelligence (AI) applications or implications. Warning: This is NOT a project for content writers or SEO bloggers. If you do not hold an academic title or cannot provide a public Google Scholar profile with previous SCI/SSCI publications, please do not bid. Scope of Work & Methodology Topic: You will propose a cutting-edge topic at the intersection of AI and MIS. Methodology (Critical): I will NOT accept simple survey-based studies analyzed onl...

I need a lightweight but highly accurate AI routine that can scan both still images or both live-streamed video & recorded videos flagging any object detection errors, noticeable colour shifts and mis-alignments in real time. The goal is simple: feed the system a stream, receive instant visual or JSON feedback on anything that doesn’t match the reference parameters I supply. Needs to be self hosted no external streaming services. My ideal workflow: • You provide a Python (or C++) module that I can drop into an existing pipeline. • It ingests common formats—JPEG/PNG for images and H.264/RTSP for video—without external conversion steps. • Object detection must identify user-defined classes with at least 95 % precision/recall on a small validation set we&...

I need an end-to-end computer-vision pipeline that can take raw tennis match footage and automatically 1) detect every player, ball, and racket on screen, and 2) classify what is happening at each moment. The pipeline must recognise player actions, tell different shot types apart, and keep consistent track of each player’s movement throughout the rally. Also with that information it must provide the strengths and tips to improve the movement and score from 0 to 100 depending of the quality of the shot. You are free to choose the stack you are most productive with—TensorFlow, PyTorch, YOLOv5/8, Detectron2, OpenCV, Deep SORT or ByteTrack are all perfectly acceptable as long as the end result is accurate and reproducible. I will supply a representative sample of matches for tra...

I have daily WRF model runs that need an automated, production-ready bias-correction layer focused on temperature. You will receive both METAR and SYNOP observations alongside several years of corresponding WRF output; your task is to turn that archive into an AI engine that improves tomorrow’s forecast before it is issued. I am specifically interested in comparing three modern approaches: • LSTM / ConvLSTM for sequence learning • Random Forest or XGBoost as tree-based baselines • Neural-network methods in a classic MOS style Feel free to blend them into a hybrid solution if that raises skill scores. During development please keep RMSE, MAE and Correlation front-of-mind; those metrics will decide which model goes operational. The final hand-off must include c...

Summary 1. Executive Summary 1.1 Product Overview AceClip is an AI-powered video clip generation platform that automatically creates engaging short-form clips from long-form videos. The platform processes YouTube videos or uploaded video files, uses AI to identify compelling moments, and generates professionally edited vertical clips optimized for social media platforms. 1.2 Key Value Propositions Automated Clip Generation: Transform long videos into multiple viral-ready clips automatically AI-Powered Intelligence: Uses speaker diarization, face tracking, and LLM analysis to identify best moments Professional Quality: Intelligent cropping, dynamic captions, and branded overlays Scalable Cloud Infrastructure: GPU-accelerated processing on for fast, concurrent job handling User-Friendly: S...

I’m looking for an AI/ML expert to build an ultra-fast model for vocal–instrument separation from WAV audio files. The goal is to achieve state-of-the-art speed and quality, outperforming existing models in both latency and accuracy. Requirements: • Strong experience with deep learning frameworks (e.g. PyTorch, TensorFlow). • Solid background in audio signal processing and spectral representations (STFT, mel-spectrograms, etc.). • Hands-on experience with source separation models (e.g. Demucs, Spleeter, ConvTasNet, or similar). • Experience optimizing models for real-time or near real-time performance (GPU/CPU optimization, quantization, batching, etc.) is a big plus. Please provide relevant work samples.

Saya sedang menyusun skripsi Ilmu Komputer dengan fokus pada Kecerdasan Buatan (AI) dan membutuhkan pendampingan menyeluruh hingga naskah final siap diuji. Ruang lingkupnya mencakup penajaman rumusan masalah, penulisan tinjauan pustaka mutakhir, perancangan metodologi eksperimen, pengolahan serta analisis data, hingga penyusunan kesimpulan dan saran. Referensi jurnal dan dataset utama sudah saya miliki, namun perlu arahan untuk menstrukturkan argumen, memilih model AI yang relevan, dan memastikan penulisan mengikuti pedoman akademik kampus (sitasi IEEE). Idealnya, Anda sudah berpengalaman mendampingi skripsi atau publikasi ilmiah di bidang machine learning atau deep learning, terbiasa dengan alat seperti Python, TensorFlow/PyTorch, Jupyter Notebook, dan Mendeley/Zotero untuk manajemen r...

Looking for a senior level A.S.R. Engineer / Programmer independent contractor -I.C. (NO agency no firms) with extensive experience (5+ years) in speech recognition systems- with both design & development. This independent contractor (IC) must have verifiable experience with ASR Systems (this included samples of their work). PLEASE NO AGENCY NO FIRMS, only independent contractors. The selected independent contractor will have extensive experience in SPEECH Recognition Systems that can recognize and assess speech- Speech Analysis. This is NOT a Speech-to-Text project, NO. This is speech recognition and analysis. An example of what is needed: ASR Systems that are used in security to validate the speech of an individual would be comparable skills set and technical features needed. ...

I have a collection of images that need precise object annotation. Every identifiable object in each frame must be enclosed with an accurate bounding box so the dataset can feed straight into my computer-vision pipeline for detection and training. I do not need facial tagging, scene classification, polygons, or key-point work—only clear, tight bounding boxes around the objects themselves. You may use tools such as LabelImg, CVAT, VoTT, or any comparable platform as long as the final export remains consistent and easy to ingest (Pascal VOC XML, COCO JSON, or YOLO text are all acceptable). Deliverables: • Fully annotated image set with bounding boxes for every object • Corresponding annotation files in the agreed-upon format • A short summary noting the tool...

I need a skilled expert to implement and publish a CNN and GNN-based fusion model on a multimodal dataset of images and text. The primary goal is to improve classification accuracy. Requirements: - Expertise in CNNs and GNNs - Experience with multimodal datasets - Strong background in image and text data processing - Proven track record in model implementation and publication Please include relevant past work and experience in your application.

Competition: Train the Best MAGIC Base Model — $200 Prize I am launching a competition to create the best-performing custom MAGIC base model. Prize: $200 to the top entry. MAGIC (Memory Augmented Generally Intelligent Cognition) is a modular AI architecture that combines retrieval, memory, transformers, difformers, MoE routing, and multimodal adapters. Competitors will receive: * The MAGIC architecture codebase * (modifiable) * (modifiable) * Core training data that must be included in the final model Your job is to train and submit a high-quality MAGIC base that demonstrates strong reasoning, conversational ability, and benchmark performance. --- Prize $200 USD to the best submission (I may also hire or bonus follow-up work for strong contenders.) --- What You Will Receiv...

End to end help in research paper, until i publish it its related to artificial inteliigence and chatgpt and bert . How to start it what do i write, what is the format, how do we publish it and then how can i go to other workshops and events and conferences for it . i can increase the bidding amount kindly let me know

I want to make small demo Python AI Chat demo to find relative source from vector. I do not want anything fancy just poc to check how its working.. need simple demo. i will share document for clear requiremnt in chat Budget - 5K