no code implementations • 29 Mar 2024 • Amitangshu Mukherjee, Timur Ibrayev, Kaushik Roy
Current Deep Neural Networks are vulnerable to adversarial examples, which alter their predictions by adding carefully crafted noise.
no code implementations • 24 Mar 2024 • Timur Ibrayev, Amitangshu Mukherjee, Sai Aparna Aketi, Kaushik Roy
Specifically, the proposed framework models the following mechanisms: 1) ventral (what) stream focusing on the input regions perceived by the fovea part of an eye (foveation), 2) dorsal (where) stream providing visual guidance, and 3) iterative processing of the two streams to calibrate visual focus and process the sequence of focused image patches.
no code implementations • 19 Mar 2024 • Timur Ibrayev, Isha Garg, Indranil Chakraborty, Kaushik Roy
sparsity is then achieved by regularizing the variance of $L_{0}$ norms of neighboring columns within the same crossbar.
no code implementations • 31 Jan 2024 • Chun Tao, Timur Ibrayev, Kaushik Roy
To mitigate this gap, we introduce the concept of "image grammar", consisting of "image semantics" and "image syntax", to denote the semantics of parts or patches of an image and the order in which these parts are arranged to create a meaningful object.
no code implementations • 27 Aug 2020 • Deboleena Roy, Indranil Chakraborty, Timur Ibrayev, Kaushik Roy
The increasing computational demand of Deep Learning has propelled research in special-purpose inference accelerators based on emerging non-volatile memory (NVM) technologies.
no code implementations • 24 Sep 2017 • Timur Ibrayev, Ulan Myrzakhan, Olga Krestinskaya, Aidana Irmanova, Alex Pappachen James
Hierarchical Temporal Memory is a new machine learning algorithm intended to mimic the working principle of neocortex, part of the human brain, which is responsible for learning, classification, and making predictions.
Emerging Technologies