ViTs are Everywhere: A Comprehensive Study Showcasing Vision Transformers in Different Domain

no code implementations • 9 Oct 2023 • Md Sohag Mia, Abu Bakor Hayat Arnob, Abdu Naim, Abdullah Al Bary Voban, Md Shariful Islam

Transformer-based models outperform other types of networks, such as convolutional and recurrent neural networks, in a range of visual benchmarks.

Image Classification Image Denoising +2

DANet: Enhancing Small Object Detection through an Efficient Deformable Attention Network

no code implementations • 9 Oct 2023 • Md Sohag Mia, Abdullah Al Bary Voban, Abu Bakor Hayat Arnob, Abdu Naim, Md Kawsar Ahmed, Md Shariful Islam

Simultaneously, when evaluated on the Pascal VOC dataset, our model showcases its ability to detect objects across a wide spectrum of categories within complex and small scenes.

object-detection Small Object Detection

EnHMM: On the Use of Ensemble HMMs and Stack Traces to Predict the Reassignment of Bug Report Fields

no code implementations • 15 Mar 2021 • Md Shariful Islam, Abdelwahab Hamou-Lhadj, Korosh K. Sabor, Mohammad Hamdaqa, Haipeng Cai

Finally, when comparing EnHMM to Im. ML. KNN, a recent approach in the field, we found that the average F-measure score of EnHMM improves the average F-measure of Im. ML. KNN by 6. 80% and improves the average recall of Im. ML. KNN by 36. 09%.

Bug fixing