T. Dam, S. Bhargav,  S. Alam, N. lilith, S. Chakraborty and M. Feroskhan, “AYDIV: Adaptable Yielding 3D Object Detection via Integrated Contextual Vision Transformer " IEEE ICRA 24, Japan (Accepted).| Link|

G. Y. Lee,  T. Dam, P. D. Poenar, N. V. Duong and Md M. Ferdaus, (2024) "HELA-VFA: A Hellinger Distance-Attention-based Feature Aggregation Network for Few Shot Classification" IEEE WACV 24, USA . | Link|

A. K. Kamath, T. Dam, H. L. Maurya, P. Singh, R. R. Nair and S. Nahavandi "Modelling and Sliding Mode Control of a Stereo Vision Augmented 6 DoF Quadrotor System"  IEEE ICAR 2023, Dubai.  | Link|

Md. R. Sarkar, S.G.  Anavatti, T. Dam, M. Pratama and B. Al Kindhi ,“Enhancing Wind Power Forecast Precision via Multi-Head Attention Transformer: An Investigation on Single-Step and Multi-Step Forecasting”,  In IEEE International Joint Conference on Neural Networks (IEEE IJCNN 23), Australia. | Link|

T. Dam, Md M. Ferdaus, M. Pratama , S.G. Anavatti, S. Jayavelu, H.A.Abbass “Latent Preserving Generative Adversarial Networks for Imbalance classification”,  In 29th IEEE International Conference on Image Processing (IEEE ICIP 2022), France. | Link|

H. Boonlia, T. Dam, Md M. Ferdaus, S.G. Anavatti, A. Mullick “Improving Self-supervised Learning for Out-of-distribution Task via Auxiliary Classifier” In 29th IEEE International Conference on Image Processing (IEEE ICIP 2022) , France.| Link|

T. Dam*, M. Pratama*, Md M. Ferdaus*, S.G. Anavatti, and H.A.Abbass “Scalable Adversarial Continual Learning”,  In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2022 (ECML PKDD 2022), France.|Link|

T. Dam, Md M. Ferdaus, S.G. Anavatti, S. Jayavelu, H.A.Abbass “Does adversarial oversampling help us?” In Proceedings of the 30th ACM International Conference on Information & Knowledge Management(CIKM 21), pp. 2970-2973. 2021, Australia.| Link|

S. Dey, and T. Dam, "Rainfall-runoff prediction using a Gustafson-Kessel clustering based Takagi-Sugeno Fuzzy model." In 2021 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1-8. IEEE, 2021 USA. | Link|

A. Mullick, S. Pal, , P. Chanda, A. Panigrahy,  A. Bharadwaj,   S. Singh and T. Dam, "D-FJ: Deep neural network based factuality judgment."  In Technology, 50, p.173, SIGKDD, 2019, USA. | Link|

T. Dam  and A. Deb," Interval type-2 modified fuzzy c-regression model clustering algorithm in TS Fuzzy Model Identification," In IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1671-1676). IEEE, 2016, Canada | Link|

 T. Dam  and A. Deb, "Block sparse representations in modified fuzzy c-regression model clustering algorithm for ts fuzzy model identification". In IEEE Symposium Series on Computational Intelligence(SSCI) (pp. 1687-1694). IEEE, 2015, South Africa| Link|

T. Dam  and A. Deb," Interval type-2 recursive fuzzy C-means clustering algorithm in the TS fuzzy model identification."  In IEEE Symposium Series on Computational Intelligence(SSCI) (pp. 22-29). IEEE, 2015, South Africa | Link|

T. Dam  and A. Deb," TS fuzzy model identification by a novel objective function based fuzzy clustering algorithm."  In IEEE Symposium Series on Computational Intelligence (SSCI)(pp. 1-7). IEEE, 2014, USA | Link|

A. Deb and T. Dam ,"A Web based Analog Signals, Network and Measurement Laboratory,"  Int. Conf. on Soft Computing, Artificial Intelligence, Pattern Recognition, Biomedical Engineering and Associated Technologies (SAP-BEATS) , 2013, India| Link|

 T. Dam, A. K. Deb. (2017),"A clustering algorithm based TS fuzzy model for tracking dynamical system data", Journal of the Franklin Institute, Vol. 354, Issue 13, pp. 5617-5645. 

 T. Dam, S.G. Anavatti and H.A.Abbass. (2020) ``Mixture of Spectral Generative Adversarial Networks for Imbalanced Hyperspectral Image Classification,” IEEE Geoscience and Remote Sensing Letters. DOI: 10.1109/LGRS.2020.3041864 | Link

 G. Y. Lee,  T. Dam, Md M. Ferdaus, P. D. Poenar, and  N. V. Duong, (2023) “WATT-EffNet: A Lightweight and Accurate Model for Classifying Aerial Disaster Images" IEEE Geoscience and Remote Sensing Letters (Accepted). | Link

 Md. R. Sarkar, S.G.  Anavatti, T. Dam, Md M. Ferdaus, M. Thatali, S. Ramasamy  and M. Pratama "GATE: A Guided Approach for Time Series Ensemble Forecasting" Expert Systems With Applications (Accepted) | Link

 Md M. Ferdaus*, T. Dam* , Z. Lim, S. Alam, S.G. Anavatti, and H.A.Abbass “Two-Player Adversarial Oversampling Strategies for Detecting Extremely Imbalanced Air-Traffic Holdings and Delays" Information Fusion (Submitted).

 Md M. Ferdaus, T. Dam, S. Alam, and D.T. Pham, “X-FUZZ: Towards a Trustworthy Evolving Neuro-fuzzy System" IEEE Transactions on Artificial Intelligence (Accepted). Link

  G. Y. Lee,  T. Dam, Md M. Ferdaus, P. D. Poenar, and  N. V. Duong,  “Unlocking the capabilities of explainable fewshot learning in remote sensing " Aritificial Intelligence Review (Accepted). Arxiv

T. Dam, S.G. Anavatti and H.A.Abbass , ”Improving ClusterGAN Using Self-Augmented Information Maximization of Disentangling Latent Spaces” , Arxiv 

 T. Dam, N. Swami, S.G. Anavatti and H.A.Abbass , ”Multi-fake evolutionary generative adversarial networks for imbalance hyper-spectral classification " , Arxiv