laguador 2013
111429139
DEVELOPING STUDENTS' ATTITUDE LEADING TOWARDS A LIFE CHANGING CAREER
It is the role of the Higher Education Institutions (HEIs) to shape the values and character of the university students to prepare them in a life changing professional career in the future. Knowledge and skills are significant aspects in every line of work but possessing the right attitude binds together all the positive thoughts leading towards the achievement of personal and professional growth. Several student programs and activities would address the needs of building the right marker of success in the quality of graduates that academic institutions yield year after year. This article provides several attitudes that would trigger positively the behavior of the students to become aware of the significant objectives of their college activities that would serve as their training ground leading towards their goal of achieving excellence. Looking forward to their future is the best way of honing their line of thinking and strengthening their feelings moving towards a commitment to quality.
Jake M Laguador
167610547
Engineering Students' Academic and on the Job Training Performance Appraisal Analysis
This study determined the level of academic performance and OJT performance based on the assessment of immediate superiors of 233 engineering student trainees from Lyceum of the Philippines University (LPU) in Batangas City. This research utilized the quantitative descriptive as well as qualitative methods of research and data were collected using documentary analysis of computed grades and comments from the employers. LPU Engineering students as observed by their immediate superiors were courteous, honest, have good moral character, with self efficacy, good in oral communication, patient and positive thinkers. Mechanical engineering students who performed well in their assigned task during their OJTs also obtained notable ratings in general and professional education courses. It is contrary to the finding that the performance of Industrial Engineering students who obtained higher academic ratings have lower job performance. The researcher formulated an Internship manual that would serve as a guide for the training of the students in the four engineering programs of LPU.
Jake M Laguador
178304443
A Correlation Study of Personal Entrepreneurial Competency and the Academic Performance in Operations Management of Business Administration Students
This study aimed to determine the Academic Performance of the Business Administration 3 rd Year students in Operations Management course in terms of the result of their Prelim Exam, Midterm Exam, and Semi Final Exam. It also analyzed the Personal Entrepreneurial Competency rating. Results showed that the Business Administration students major in Human Resource Development and Management obtained low score in Prelim and Midterm examination where they find it difficult to answer Math problems. Goal setting, Information seeking and Persistence are the Personal Entrepreneurial Competencies where the students obtained high scores. The demand for quality and information seeking revealed significant relationship in two major examinations in Operations Management.
Jake M Laguador
109621360
Tracer study of BS computer engineering graduates of Lyceum of the Philippines University
This tracer study is intended to assess the present employment status of the Computer Engineering graduates and the relevance of curriculum, knowledge, skills, work values and school related factors to their job placement. Descriptive type of research method was used in the study with 175 computer engineering graduates served as respondents. Results showed that majority of the Computer Engineering graduates are gainfully employed with present positions related to course completed and had obtained their first job within 1 to 6 months in local manufacturing firms as walk in applicants. Mathematics is considered the most relevant among the general education subjects and Microsoft Office Application, Computer Troubleshooting/Maintenance and Computer Programming are the three most relevant professional subjects to their present employment. Information Technology and communication skills were deemed to be the most useful competencies learned by the graduates from LPU and the work related values such as perseverance and hard work have also greatly contributed to their job placement.
Jake M Laguador Conrado I Dotong
206777226
ICDAR 2013 Robust Reading Competition
This report presents the final results of the ICDAR 2013 Robust Reading Competition. The competition is structured in three Challenges addressing text extraction in different application domains, namely born digital images, real scene images and real scene videos. The Challenges are organised around specific tasks covering text localisation, text segmentation and word recognition. The competition took place in the first quarter of 2013, and received a total of 42 submissions over the different tasks offered. This report describes the datasets and ground truth specification, details the performance evaluation protocols used and presents the final results along with a brief summary of the participating methods.
2013 12th International Conference on Document Analysis and Recognition
Dimosthenis Karatzas Faisal Shafait Seiichi Uchida M Iwamura Lluis Gomez i Bigorda Sergi Robles Mestre Joan Mas Romeu David Fernandez Mota Jon Almazan Lluis-Pere de las Heras
7495339
300 Faces in the Wild Challenge: The First Facial Landmark Localization Challenge
Automatic facial point detection plays arguably the most important role in face analysis. Several methods have been proposed which reported their results on databases of both constrained and unconstrained conditions. Most of these databases provide annotations with different mark ups and in some cases the are problems related to the accuracy of the fiducial points. The aforementioned issues as well as the lack of a evaluation protocol makes it difficult to compare performance between different systems. In this paper, we present the 300 Faces in the Wild Challenge: The first facial landmark localization Challenge which is held in conjunction with the International Conference on Computer Vision 2013, Sydney, Australia. The main goal of this challenge is to compare the performance of different methods on a new collected dataset using the same evaluation protocol and the same mark up and hence to develop the first standardized benchmark for facial landmark localization.
2013 IEEE International Conference on Computer Vision Workshops
Christos Sagonas Georgios Tzimiropoulos Stefanos Zafeiriou Maja Pantic
13953660
New types of deep neural network learning for speech recognition and related applications: an overview
In this paper, we provide an overview of the invited and contributed papers presented at the special session at ICASSP 2013, entitled "New Types of Deep Neural Network Learning for Speech Recognition and Related Applications," as organized by the authors. We also describe the historical context in which acoustic models based on deep neural networks have been developed. The technical overview of the papers presented in our special session is organized into five ways of improving deep learning methods: (1) better optimization; (2) better types of neural activation function and better network architectures; (3) better ways to determine the myriad hyper parameters of deep neural networks; (4) more appropriate ways to preprocess speech for deep neural networks; and (5) ways of leveraging multiple languages or dialects that are more easily achieved with deep neural networks than with Gaussian mixture models.
2013 IEEE International Conference on Acoustics, Speech and Signal Processing
Li Deng Geoffrey E Hinton Brian Kingsbury
700906
Detection of traffic signs in real world images: The German traffic sign detection benchmark
Real time detection of traffic signs, the task of pinpointing a traffic sign's location in natural images, is a challenging computer vision task of high industrial relevance. Various algorithms have been proposed, and advanced driver assistance systems supporting detection and recognition of traffic signs have reached the market. Despite the many competing approaches, there is no clear consensus on what the state of the art in this field is. This can be accounted to the lack of comprehensive, unbiased comparisons of those methods. We aim at closing this gap by the "German Traffic Sign Detection Benchmark" presented as a competition at IJCNN 2013 (International Joint Conference on Neural Networks) We introduce a real world benchmark data set for traffic sign detection together with carefully chosen evaluation metrics, baseline results, and a web interface for comparing approaches. In our evaluation, we separate sign detection from classification, but still measure the performance on relevant categories of signs to allow for benchmarking specialized solutions. The considered baseline algorithms represent some of the most popular detection approaches such as the Viola Jones detector based on Haar features and a linear classifier relying on HOG descriptors. Further, a recently proposed problem specific algorithm exploiting shape and color in a model based Houghlike voting scheme is evaluated. Finally, we present the best performing algorithms of the IJCNN competition.
The 2013 International Joint Conference on Neural Networks (IJCNN)
Sebastian Houben Johannes Stallkamp Jan Salmen Marc Schlipsing C Igel
12350611
NEIL: Extracting Visual Knowledge from Web Data
We propose NEIL (Never Ending Image Learner) a computer program that runs 24 hours per day and 7 days per week to automatically extract visual knowledge from Internet data. NEIL uses a semi supervised learning algorithm that jointly discovers common sense relationships (e.g. "Corolla is a kind of/looks similar to Car" "Wheel is a part of Car" and labels instances of the given visual categories. It is an attempt to develop the world's largest visual structured knowledge base with minimum human labeling effort. As of 10th October 2013, NEIL has been continuously running for 2.5 months on 200 core cluster (more than 350K CPU hours) and has an ontology of 1152 object categories, 1034 scene categories and 87 attributes. During this period, NEIL has discovered more than 1700 relationships and has labeled more than 400K visual instances.
2013 IEEE International Conference on Computer Vision
Xinlei Chen Abhinav Shrivastava Abhinav Gupta
206553432
Standard Particle Swarm Optimisation 2011 at CEC 2013: A baseline for future PSO improvements
In this work we benchmark, for the first time, the latest Standard Particle Swarm Optimisation algorithm (SPSO 2011) against the 28 test functions designed for the Special Session on Real Parameter Single Objective Optimisation at CEC 2013. SPSO 2011 is a major improvement over previous PSO versions, with an adaptive random topology and rotational invariance constituting the main advancements. Results showed an outstanding performance of SPSO 2011 for the family of unimodal and separable test functions, with a fast convergence to the global optimum, while good performance was observed for four rotated multimodal functions. Conversely, SPSO 2011 showed the weakest performance for all composition problems (i.e. highly complex functions specially designed for this competition) and certain multimodal test functions. In general, a fast convergence towards the region of the global optimum was achieved, requiring less than 10E+03 function evaluations. However, for most composition and multimodal functions SPSO2011 showed a limited capability to "escape" from sub optimal regions. Despite this limitation, a desirable feature of SPSO 2011 was its scalable behaviour, which observed up to 50 dimensional problems, i.e. keeping a similar performance across dimensions with no need for increasing the population size. Therefore, it seems advisable that future PSO improvements be focused on enhancing the algorithm's ability to solve non separable and asymmetrical functions, with a large number of local minima and a second global minimum located far from the true optimum. This work is the first effort towards providing a baseline for a fair comparison of future PSO improvements.
2013 IEEE Congress on Evolutionary Computation
Mauricio Zambrano-Bigiarini Maurice Clerc Rodrigo Rojas-Mujica