Search Results for "face recognition" - Page 4

Our project is related to face recognition...

Libface is a cross platform framework for developing face recognition algorithms and testing its performance.

1>Face Recognition on real-time based. 2>shirt -color recognition on image based.

Face recognition with HMM.

Artificial neural network with eigenfaces for face recognition

An open source face recognition project.

Active Shape/Appearance Model Library (ASMLibrary/AAMLibrary) source code, which includes ASMBuilding/AAMBuilding as well as ASMFitting/AAMFitting algorithm. It is developped under OpenCV 1.0 for locating features in a face and face recognition.

System using to verify personality by face's photo.

Java framework for face detection and face recognition based on different plugin and filter types. Includes Eigenfaces in pure Java, OpenCV detection via JNI, integration of the Betaface.com Web Service, skin color filter, Adobe XMP Export and a nice GUI

OpenNeuron is a neural networks implementation written in Java. Currently supports only Kohonen Network model, but API is designed to be easily extended to model other network types. This implementation was used for face thermal pictures recognition.

BioAuth is an application which tries to use face detection and recognition algorithms.

Malic is realtime face recognition system that based on Malib and CSU Face Identification Evaluation System (csuFaceIdEval). Uses Malib library for realtime image processing and some of csuFaceIdEval for face recognition.

StReAV is a software which runs on Linux, loaded onto a PDA/handheld, into which the an audio and video capturing tool which could be easily clamped onto the collar of a shirt is connected. Capture or stream your video, even use it for face recognition.

Compression of face images impact the performance of face recognition (FR) systems. JPEG Region of Interest (JROI) compression maintains high image quality in facial regions while compressing the background more, with minimal impact on FR performance.

The OpenCV DLLCapture project goal is to provide an easy way for using the Intel OpenCV library face recognition feature within custom built applications.

FaceTracker is a webcam-based system for the recognition of face movement around various angles as well as translation of the face. It is intended to be used under Linux OS. Currently, pan angles can be detected up to 45 degrees.

The development of a biometric system and applications e.g. Access Control based on the system to recognize and verify people. The primary goal is face recognition, but other human attributes might get used too in the future.

WRChat is a fast and lightweight single room chat system for the web where lots of people can join in and talk to each other. Its main features are: Frames , Newest messages first, ASCII happy face recognition, User registration, preferences, internal mai

WHAY is a Video-based Face Recognition tool written in MATLAB. It aims to exploits PCA recognizing as better as possible and tests the limits of this approach.

wav2vec2-large-xlsr-53-portuguese is an automatic speech recognition (ASR) model fine-tuned on Portuguese using the Common Voice 6.1 dataset. It is based on Facebook’s wav2vec2-large-xlsr-53, a multilingual self-supervised learning model, and is optimized to transcribe Portuguese speech sampled at 16kHz. The model performs well without a language model, though adding one can improve word error rate (WER) and character error rate (CER).

...The model supports both PyTorch and JAX and is compatible with the Hugging Face Transformers and HuggingSound libraries. It is ideal for Russian voice transcription tasks in research, accessibility, and interface development. The training was made possible with compute support from OVHcloud, and the training scripts are publicly available for replication.

layoutlm-base-uncased is a multimodal transformer model developed by Microsoft for document image understanding tasks. It incorporates both text and layout (position) features to effectively process structured documents like forms, invoices, and receipts. This base version has 113 million parameters and is pre-trained on 11 million documents from the IIT-CDIP dataset. LayoutLM enables better performance in tasks where the spatial arrangement of text plays a crucial role. The model uses a...

Bio_ClinicalBERT is a domain-specific language model tailored for clinical natural language processing (NLP), extending BioBERT with additional training on clinical notes. It was initialized from BioBERT-Base v1.0 and further pre-trained on all clinical notes from the MIMIC-III database (~880M words), which includes ICU patient records. The training focused on improving performance in tasks like named entity recognition and natural language inference within the healthcare domain. Notes were...