Colloquium Archive

Automatically Localizing The Relevant Image Regions For Weakly-Supervised Visual Recognition

Yong Jae Lee, University of California, Davis


Our group's recent and ongoing work on weakly-supervised visual recognition will be presented. In contrast to fully-supervised algorithms, the proposed methods do not require detailed localization annotations during training, and instead can learn to attend to the relevant visual regions given only image-level semantic tags that state whether an object is present or absent in the image (e.g. an image tagged with "car") or pairwise comparisons that state whether one image has more of a visual property than the other ("person A is more smiling than person B"). I will show how the proposed algorithms can produce state-of-the-art weakly-supervised results for object detection and attribute modeling, and can sometimes reach accuracy that is (nearly) on par with fully-supervised methods at a fraction of the annotation cost.

Time-Efficient Information Collection In Rfid Networks

Hao Yue, San Francisco State University


Radio-frequency Identification (RFID) networks nowadays have been widely used in various cyber-physical systems in the fields such as manufacturing, transportation, energy, and healthcare, for identification, tracking, and information collection due to the simplicity and low cost of RFID tags. For these cyber-physical systems, time-efficient information collection is usually desirable or even a must, but highly challenging with RFID networks because the hardware of tags is too simple to support sophisticated protocol operations and naive solutions suffer severe transmission collisions and significant communication overhead. In this talk, a new protocol for time-efficient information collection in RFID networks is presented. By using several new and lightweight techniques such as Bloom filtering and hash functions, the protocol successfully removes the unnecessary time-consuming transmissions of tag IDs in naive solutions and also efficiently minimizes transmission collisions, which drastically reduces the time and communication overhead for information collection.

No, Seriously, What Is A Monad?

Jason Shankel, Sr. Gameplay Engineer @ FableLabs


Functional programming has experienced a surge in mainstream software development in recent years. I will cover the basics of functional programming, emergence of the new mixed functional/imperative paradigm and answer the burning question, just what the heck is a monad anyway?

Hybrid Ecologies: Disobedient Objects, Unexpected Landscapes, And Human Wonderment

Eric Paulos, University of California, Berkeley


This talk will present and critique a new body of evolving collaborative work at the intersection of art, computer science, and design research. It will present an argument for hybrid materials, methods, and artifacts as strategic tools for insight and innovation within computing culture. The narrative will present specific new work across three primary themes: (1) the New Making Renaissance, (2) Participation, Activism, and Micro-Volunteerism, (3) Neo-Wearables inducing Epidermis and Cosmetic Computing, and (4) Bio-Electric Hybrids. Finally, it will present and question emerging materials and strategies from the perspective of engineering, design, and new media

Trends In Automotive Security

Bruce Edward DeBruhl, California Polytechnic State University, San Luis Obispo


In 1913 the introduction of the assembly line enabled the mass production of personal vehicles that revolutionized the world. Personal vehicles have, traditionally, been self-contained such that all communications were internal to the car. Because of this, automotive security has previously focused on 2 tasks: preventing theft and improving vehicle safety. With continued growth of vehicle-to-vehicle communications, automotive security has now fundamentally changed. To secure tomorrow’s vehicles, it is necessary to reconsider how we design and secure cars. In this talk, we discuss the security implications of recent trends in collaborative and autonomous vehicles.