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Found 23 papers, 15 papers with code
Shadow: A Novel Loss Function for Efficient Training in Siamese Networks
Its effectiveness and robustness across balanced, imbalanced, medical, and non-medical image datasets suggests that it is not specific to a particular model or dataset but demonstrates superior performance consistently while using less memory and computation.
BanLemma: A Word Formation Dependent Rule and Dictionary Based Bangla Lemmatizer
Lemmatization holds significance in both natural language processing (NLP) and linguistics, as it effectively decreases data density and aids in comprehending contextual meaning.
ChatGPT-guided Semantics for Zero-shot Learning
Then, we enrich word vectors by combining the word embeddings from class names and descriptions generated by ChatGPT.
LumiNet: The Bright Side of Perceptual Knowledge Distillation
In knowledge distillation literature, feature-based methods have dominated due to their ability to effectively tap into extensive teacher models.
Ranked #1 on
Classification
on CIFAR-100
CosSIF: Cosine similarity-based image filtering to overcome low inter-class variation in synthetic medical image datasets
FBGT involves the removal of real images that exhibit similarities to images of other classes before utilizing them as the training dataset for a GAN.
SentiGOLD: A Large Bangla Gold Standard Multi-Domain Sentiment Analysis Dataset and its Evaluation
This study introduces SentiGOLD, a Bangla multi-domain sentiment analysis dataset.
BenCoref: A Multi-Domain Dataset of Nominal Phrases and Pronominal Reference Annotations
While widely studied for English and other resource-rich languages, research on coreference resolution in Bengali largely remains unexplored due to the absence of relevant datasets.
COLT: Cyclic Overlapping Lottery Tickets for Faster Pruning of Convolutional Neural Networks
This research aims to generate winning lottery tickets from a set of lottery tickets that can achieve similar accuracy to the original unpruned network.
LMFLOSS: A Hybrid Loss For Imbalanced Medical Image Classification
In this study, we propose a novel loss function to train neural network models to mitigate this critical issue in this important field.
Knowledge Distillation approach towards Melanoma Detection
As well as with fewer learnable parameters, 0. 26 million (M) compared to 42. 5M using knowledge distillation with the goal to detect melanoma from dermoscopic images.
Less is More: Facial Landmarks can Recognize a Spontaneous Smile
Smile veracity classification is a task of interpreting social interactions.
Bangla-Wave: Improving Bangla Automatic Speech Recognition Utilizing N-gram Language Models
Although over 300M around the world speak Bangla, scant work has been done in improving Bangla voice-to-text transcription due to Bangla being a low-resource language.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Rethinking Task-Incremental Learning Baselines
A common goal of task-incremental methods is to design a network that can operate on minimal size, maintaining decent performance.
LILA-BOTI : Leveraging Isolated Letter Accumulations By Ordering Teacher Insights for Bangla Handwriting Recognition
Word-level handwritten optical character recognition (OCR) remains a challenge for morphologically rich languages like Bangla.
VISTA: Vision Transformer enhanced by U-Net and Image Colorfulness Frame Filtration for Automatic Retail Checkout
Multi-class product counting and recognition identifies product items from images or videos for automated retail checkout.
Dynamic Rectification Knowledge Distillation
This approach of distilling knowledge has gained popularity as a result of the prohibitively complicated nature of such cumbersome models for deployment on edge computing devices.
Curricular SincNet: Towards Robust Deep Speaker Recognition by Emphasizing Hard Samples in Latent Space
The advantage of such a curriculum learning-based techniques is that it will impose inter-class margins as well as taking to account easy and hard samples.
ViPTT-Net: Video pretraining of spatio-temporal model for tuberculosis type classification from chest CT scans
We explore the idea of whether pretraining a model on realistic videos could improve performance rather than training the model from scratch, intended for tuberculosis type classification from chest CT scans.
Bi-FPNFAS: Bi-Directional Feature Pyramid Network for Pixel-Wise Face Anti-Spoofing by Leveraging Fourier Spectra
The emergence of biometric-based authentication using modern sensors on electronic devices has led to an escalated use of face recognition technologies.
Ranked #1 on
Face Anti-Spoofing
on OULU-NPU
A-DeepPixBis: Attentional Angular Margin for Face Anti-Spoofing
Face Anti Spoofing (FAS) systems are used to identify malicious spoofing attempts targeting face recognition systems using mediums such as video replay or printed papers.
Ranked #3 on
Face Anti-Spoofing
on OULU-NPU
Uniformizing Techniques to Process CT scans with 3D CNNs for Tuberculosis Prediction
A common approach to medical image analysis on volumetric data uses deep 2D convolutional neural networks (CNNs).
Chittron: An Automatic Bangla Image Captioning System
The results show that the model has successfully been able to learn a working language model and to generate captions of images quite accurately in many cases.
BanglaLekha-Isolated: A Comprehensive Bangla Handwritten Character Dataset
Bangla handwriting recognition is becoming a very important issue nowadays.
