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Found 7 papers, 1 papers with code
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must be covered in more detail.
MUNCH: Modelling Unique 'N Controllable Heads
We propose a method that offers quality, diversity, control, and realism along with explainable network design, all desirable features to game-design artists in the domain.
An Object Aware Hybrid U-Net for Breast Tumour Annotation
For polygon like annotation or segmentation, we have used Active Contours whose vertices or snake points move towards the boundary of the object of interest to find the region of minimum energy.
Bag of Visual Words (BoVW) with Deep Features -- Patch Classification Model for Limited Dataset of Breast Tumours
BoVW is used as a feature selector to select most discriminative features among the CNN features.
Ensembling Handcrafted Features with Deep Features: An Analytical Study for Classification of Routine Colon Cancer Histopathological Nuclei Images
The use of Deep Learning (DL) based methods in medical histopathology images have been one of the most sought after solutions to classify, segment, and detect diseased biopsy samples.
Cell nuclei classification in histopathological images using hybrid OLConvNet
To further strengthen the viability of our architectural approach, we tested our proposed methodology with state of the art deep learning architectures AlexNet, VGG16, VGG19, ResNet50, InceptionV3, and DenseNet121 as backbone networks.
An End-to-End Breast Tumour Classification Model Using Context-Based Patch Modelling- A BiLSTM Approach for Image Classification
However, due to patch-based analysis, most of the current methods fail to exploit the underlying spatial relationship among the patches.
