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20182020
most citedMixing ADAM and SGD: a Combined Optimization Method

18 citations · 35 across the 14 of their papers we have counts for

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Showing 2018Show all

5 papers · 1 filter

cs.CV2018

Learning Inward Scaled Hypersphere Embedding: Exploring Projections in Higher Dimensions

Muhammad Kamran Janjua, Shah Nawaz, Alessandro Calefati +1

Majority of the current dimensionality reduction or retrieval techniques rely on embedding the learned feature representations onto a computable metric space. Once the learned feat…

cs.CV2018★ 1 cited

Image and Encoded Text Fusion for Multi-Modal Classification

Ignazio Gallo, Alessandro Calefati, Shah Nawaz +1

Multi-modal approaches employ data from multiple input streams such as textual and visual domains. Deep neural networks have been successfully employed for these approaches. In thi…

cs.CV2018★ 1 cited

Seeing Colors: Learning Semantic Text Encoding for Classification

Shah Nawaz, Alessandro Calefati, Muhammad Kamran Janjua +1

The question we answer with this work is: can we convert a text document into an image to exploit best image classification models to classify documents? To answer this question we…

cs.CV2018★ 10 cited

Git Loss for Deep Face Recognition

Alessandro Calefati, Muhammad Kamran Janjua, Shah Nawaz +1

Convolutional Neural Networks (CNNs) have been widely used in computer vision tasks, such as face recognition and verification, and have achieved state-of-the-art results due to th…

cs.CV2018★ 4 cited

Revisiting Cross Modal Retrieval

Shah Nawaz, Muhammad Kamran Janjua, Alessandro Calefati +1

This paper proposes a cross-modal retrieval system that leverages on image and text encoding. Most multimodal architectures employ separate networks for each modality to capture th…