Publications related to Convolutional neural network

As an 'early alerting' sense, one of the primary tasks for the human visual system is to recognize distant objects. In the specific context of facial identification, this ecologically important task has received surprisingly little attention. Most studies ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Rigidity-Aware Detection for 6D Object Pose Estimation

Mathieu Salzmann, Yinlin Hu, Jingyu Li, Rui Song

Most recent 6D object pose estimation methods first use object detection to obtain 2D bounding boxes before actually regressing the pose. However, the general object detection methods they use are ill-suited to handle cluttered scenes, thus producing poor ...

Los Alamitos2023

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Silvestro Micera, Simone Romeni, Elena Losanno, Luca Pierantoni

Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon ...

IOP Publishing Ltd2023

4M: Massively Multimodal Masked Modeling

Shuqing Teresa Yeo, Amir Roshan Zamir, Oguzhan Fatih Kar, Roman Christian Bachmann, David Mizrahi

Current machine learning models for vision are often highly specialized and limited to a single modality and task. In contrast, recent large language models exhibit a wide range of capabilities, hinting at a possibility for similarly versatile models in co ...

Neural Information Processing Systems (Nips)2023

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Mathias Josef Payer, Zhiyao Feng, Chunmin Zhang, Ji Shi

Knowledge of a program's input format is essential for effective input generation in fuzzing. Automated input format reverse engineering represents an attractive but challenging approach to learning the format. In this paper, we address several challenges ...

Berkeley2023

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Alfio Quarteroni, Andrea Manzoni

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Hoboken2023

A multichannel versatile brain activity classification and closed loop neuromodulation system, device and method using a highly multiplexed mixed-signal front-end

Mahsa Shoaran, Uisub Shin, Bingzhao Zhu

A closed-loop neuromodulation system, including an electrode array that is implantable to a brain of a subject, analog front-end device (AFD) for selectively selecting and reading a plurality of channels from electrode array, a finite impulse response (FIR ...

2023

A new age in protein design empowered by deep learning

Bruno Emanuel Ferreira De Sousa Correia, Michael Bronstein, Hamed Khakzad, Casper Alexander Goverde, Arne Schneuing, Ilia Igashov

The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

Cambridge2023

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Convolutional neural network

Recognizing distant faces

Rigidity-Aware Detection for 6D Object Pose Estimation

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

4M: Massively Multimodal Masked Modeling

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Probabilistic methods for neural combinatorial optimization

Multi-agent Reinforcement Learning for Assembly of a Spanning Structure

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

A multichannel versatile brain activity classification and closed loop neuromodulation system, device and method using a highly multiplexed mixed-signal front-end

A new age in protein design empowered by deep learning

Graph Chatbot

Chat with Graph Search

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Rigidity-Aware Detection for 6D Object Pose Estimation

Recognizing distant faces

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

4M: Massively Multimodal Masked Modeling

Probabilistic methods for neural combinatorial optimization

Multi-agent Reinforcement Learning for Assembly of a Spanning Structure

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

A multichannel versatile brain activity classification and closed loop neuromodulation system, device and method using a highly multiplexed mixed-signal front-end

A new age in protein design empowered by deep learning