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Category Computer Science

SSD: The Single Shot MultiBox Detector – A Game-Changing Approach to Object Detection

Object detection, a crucial computer vision problem, involves locating and classifying objects within an image or video. Over the years, researchers have developed various methods to tackle this challenge. One ground-breaking approach is the Single Shot MultiBox Detector (SSD), an… Continue Reading →

Recombinator Networks: Enhancing Deep Learning Performance by Coarse-to-Fine Feature Aggregation

Deep learning has become an integral part of state-of-the-art computer vision systems, allowing machines to understand and interpret visual information. Convolutional neural networks (CNNs) with alternating layers of convolution, max-pooling, and decimation have been widely adopted in computer vision architectures…. Continue Reading →

Exploring the Computational Complexity of Decision Membership in Moment Polytopes

Understanding the computational complexity of a problem lies at the heart of solving it efficiently. In a recent research article titled “Membership in Moment Polytopes is in NP and coNP”, Peter Bürgisser, Matthias Christandl, Ketan D. Mulmuley, and Michael Walter… Continue Reading →

ALOJA: A Framework for Benchmarking and Predictive Analytics in Big Data Deployments

What is ALOJA project? The ALOJA project is a collaborative effort between the Barcelona Supercomputing Center (BSC) and Microsoft with the aim of automating the characterization of cost-effectiveness in Big Data deployments, with a specific focus on the Hadoop platform…. Continue Reading →

Understanding Submodular Functions: from Discrete to Continuous Domains

What are Submodular Set-Functions? Submodular set-functions are mathematical objects that have various applications in combinatorial optimization. These functions can be minimized and approximately maximized in polynomial time, making them valuable tools in solving optimization problems. Real-world example: Imagine you are… Continue Reading →

Temporal Dynamic Appearance Modeling: Enhancing Multi-Person Tracking with Real-Time Accuracy

In the age of advanced technology and increasing reliance on surveillance systems, the ability to accurately track multiple individuals in complex scenes is of utmost importance. With the rise of online detection technologies, the challenge lies in associating these detections… Continue Reading →

Discovering Unwarranted Associations in Data-Driven Applications

In a world where our personal data is collected and analyzed by numerous companies, the issue of unfair treatments arising from irresponsible data usage has become increasingly concerning. Decision-making entities need to be held accountable for any unfair or discriminatory… Continue Reading →

Amodal Completion and Size Constancy in Natural Scenes: Enhancing Object Detection Systems

Understanding and accurately perceiving the size and depth of objects in a scene is a fundamental aspect of visual perception. While humans possess an innate ability to make sense of our visual environment, teaching machines to do the same has… Continue Reading →

Central Pattern Generators: Versatile Control Systems for Robotics

In the constantly evolving field of robotics, bio-inspired control systems have gained significant attention due to their wide range of real-world applications. One such control system that has proven to be highly versatile for robotic systems requiring oscillatory behavior, such… Continue Reading →

Face Search at Scale: Finding Needles in a Haystack of 80 Million Faces

Social media platforms like Facebook have revolutionized how we share our lives with others, including uploading and sharing photos. With billions of photos being uploaded daily, finding specific individuals in this vast ocean of images has become a massive challenge… Continue Reading →

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