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The 25th IEEE International Conference on Image Processing (ICIP) was held in the Megaron Athens International Conference Centre, Athens, Greece, from October 7-10, 2018. ICIP is the world’s largest and most comprehensive technical conference focused on image and video processing and computer vision. The theme of ICIP 2018 will be “Imaging beyond imagination”. The conference features world-class speakers, tutorials, exhibits, and a vision technology showcase.

MCL Director, Professor C.-C. Jay Kuo, delivered the Plenary Speech entitled with “Unveil Convolutional Neural Networks (CNNs) and Go Beyond” on Oct. 8, 2018. Professor Kuo has worked on theoretical understanding of CNNs since 2015 and published a sequence of papers on this topic. This speech contained main results of his research endeavor.

Specifically, Professor Kuo described a new interpretable feedforward CNN design methodology. It does not demand any backpropagation. This design adopts a data-centric approach and derives network parameters of the current layer based on data statistics from the output of the previous layer. This process continues layer after layer in one pass. The feedforward design leads to a CNN that has a classification performance close to the one designed by backpropagation. Yet, it is more robust with respect to adversarial attacks. Above all, it is mathematically transparent.

Professor Kuo has a paper entitled with “Interpretable Convolutional Neural Networks via Feedforward Design” as the main reference. It can be downloaded from the arXiv: https://arxiv.org/abs/1810.02786.

1. Could you briefly introduce yourself and your research interests?

I am Manasa Manohara, a Master’s student at USC pursuing EE with a focus on Computer Vision. I finished my Bachelor’s from M.S.Ramaiah Institute of Technology in Bangalore, India. I worked as a Development Consultant at SAP India for about a year before I joined USC. I am excited about Computer Vision and Machine Learning, and how a combination of these technologies can be applied to solve everyday problems. I am particularly interested in Image and video segmentation and reconstruction. In my free time, I love to dance and read books.

2. What is your impression about MCL and USC?

USC provides a lot of opportunities for the students to grow not just in terms of academics but also encourages to pursue their personal interests.  It has a good mix of people who are passionate about what they do. I hope I can make the most of what USC has to offer.

MCL is doing a lot of good work in the field of Computer Vision and I would love to learn and contribute to their research along with interacting with my peers to explore their fields of interest.

3. What is your future expectation and plan in MCL?

I hope I can enhance my skills in the fields of Image Processing and Deep learning. I wish to accelerate and solve everyday persistent problems with an exciting mixture of the above technologies.

1. Could you briefly introduce yourself and your research interests?

My name is Wang, Yun Cheng, but you can simply call me Joe. I like to play basketball, and have been an authentic Lakers’ fan since my junior high. So, it’s exciting for me to be in LA. I came from Taiwan, and currently I am a master student in the electrical engineering department, USC. More specifically, I am in the multimedia and creative technology program, so basically I like to deal with various kinds of multimodal data. I have done some projects on video understanding in my undergraduate, and I hope I can keep on building my strength in multimedia analysis. Recently, I am digging into a novel research topic, network embedding. The research topic is interesting and still has a lot can be explored so I believe I can learn a lot from it. Really looking forward to being in the MCL.

2. What is your impression about MCL and USC?

MCL is a lively lab. Every member in the lab loves what they are doing. They work really hard on what they are enthusiastic about, but at the same time, they know how to enjoy their lives. I think it’s important to know how to strike a good balance between research and the ordinary life for a graduate student. And, members in MCL have just done so well. I enjoy working with the lab members, and we are still friends when we are not in the lab. Discussing with Professor Kuo is also an enjoyable experience, his taste and insight on research topics is so innovative that you can always learn something from him. The campus of USC is gorgeous. But, sometimes it [...]

1. Could you briefly introduce yourself and your research interests?

My name is Zhiruo Zhou, and I just received my bachelor’s degree in Electrical Engineering this July. Now I will start my first year at USC as a PhD student. During my undergraduate training, research projects that I got involved in were mostly about image processing, such as denoising on MRI images and image recognition tasks. Having experiences with both traditional image processing techniques and machine learning, I would like to explore more on their relationship and applications.

2. What is your impression about MCL and USC?

The sunshine here is always warm and the integral architectural style on campus makes me feel comfortable. The MCL is really a big group and has a great network. The pizza lunch and seminar on Friday are fantastic and beneficial. You can always learn from your group members and they are pleased to offer help. It’s enjoyable to know these lovely people, and I’m happy to be one of them!

3. What is your future expectation and plan in MCL?

I expect that I could gradually establish a deep understanding of machine learning and be well practiced in doing research. I might also try to refine my career plan by communicating with professors and peers. Also, I want to know more about the MCL family and make friends with them.

1. Could you briefly introduce yourself and your research interests?

My name is Chenxuan Guo. I am a junior student of Electrical and Computer Engineering department in NCTU (National Chiao Tung University). I come to MCL for an internship in summer. One of the things that I am interested is audio analysis, especially instrumental music separating and converting. Hope one day the accurate realization of audio to score (including audio to midi and midi to score) comes true. The second one is the topic of parallelized computing or distributed operating systems. I am still researching about the faster approximation of optimization of source allocation in fog computing.

2. What is your impression about MCL and USC?

I like the atmosphere of MCL, because Professor Guo’s guidance is very special, more like a father than a teacher. Everyone in the lab has their own strengths and they are good at supporting each other.

3. What is your future expectation and plan in MCL?

I hope I can finish my research in graph embedding timely this summer. With help from Pr. Kuo, Bin and Jessica. I must make a push to do my experiment.