Adewale Adeyemo
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View article: Relationship between Uncertainty in DNNs and Adversarial Attacks
Relationship between Uncertainty in DNNs and Adversarial Attacks Open
Deep Neural Networks (DNNs) have achieved state of the art results and even outperformed human accuracy in many challenging tasks, leading to DNNs adoption in a variety of fields including natural language processing, pattern recognition, …
View article: Securing Pseudo-Model Parallelism-Based Collaborative DNN Inference for Edge Devices
Securing Pseudo-Model Parallelism-Based Collaborative DNN Inference for Edge Devices Open
Collaborative Deep Neural Network Inference (CDNN) has emerged as one of the significant strategies for efficient and lightweight computation on resource-constrained devices (like drones), especially in the case of adverse events like natu…
View article: StAIn: Stealthy Avenues of Attacks on Horizontally Collaborated Convolutional Neural Network Inference and Their Mitigation
StAIn: Stealthy Avenues of Attacks on Horizontally Collaborated Convolutional Neural Network Inference and Their Mitigation Open
With significant potential improvement in device-to-device (D2D) communication due to improved wireless link capacity (e.g., 5G and NextG systems), a collaboration of multiple edge devices (called horizontal collaboration (HC)) is becoming…
View article: Towards Enabling Dynamic Convolution Neural Network Inference for Edge Intelligence
Towards Enabling Dynamic Convolution Neural Network Inference for Edge Intelligence Open
Deep learning applications have achieved great success in numerous real-world applications. Deep learning models, especially Convolution Neural Networks (CNN) are often prototyped using FPGA because it offers high power efficiency and reco…
View article: Security Analysis of Capsule Network Inference using Horizontal\n Collaboration
Security Analysis of Capsule Network Inference using Horizontal\n Collaboration Open
The traditional convolution neural networks (CNN) have several drawbacks like\nthe Picasso effect and the loss of information by the pooling layer. The\nCapsule network (CapsNet) was proposed to address these challenges because its\narchit…
View article: Security Analysis of Capsule Network Inference using Horizontal Collaboration
Security Analysis of Capsule Network Inference using Horizontal Collaboration Open
The traditional convolution neural networks (CNN) have several drawbacks like the Picasso effect and the loss of information by the pooling layer. The Capsule network (CapsNet) was proposed to address these challenges because its architect…