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Found 5 papers, 2 papers with code
IllusionVQA: A Challenging Optical Illusion Dataset for Vision Language Models
GPT4V, the best-performing VLM, achieves 62. 99% accuracy (4-shot) on the comprehension task and 49. 7% on the localization task (4-shot and Chain-of-Thought).
Ranked #1 on
Object Localization
on IllusionVQA
Connecting the Dots: Leveraging Spatio-Temporal Graph Neural Networks for Accurate Bangla Sign Language Recognition
Recent advances in Deep Learning and Computer Vision have been successfully leveraged to serve marginalized communities in various contexts.
Ophthalmic Biomarker Detection Using Ensembled Vision Transformers -- Winning Solution to IEEE SPS VIP Cup 2023
This report outlines our approach in the IEEE SPS VIP Cup 2023: Ophthalmic Biomarker Detection competition.
Bangla Grammatical Error Detection Using T5 Transformer Model
This paper presents a method for detecting grammatical errors in Bangla using a Text-to-Text Transfer Transformer (T5) Language Model, using the small variant of BanglaT5, fine-tuned on a corpus of 9385 sentences where errors were bracketed by the dedicated demarcation symbol.
Applying wav2vec2 for Speech Recognition on Bengali Common Voices Dataset
After training for 71 epochs, on a training set consisting of 36919 mp3 files, we achieved a training loss of 0. 3172 and WER of 0. 2524 on a validation set of size 7, 747.
