“…Vision d'avenir pour un Canada fort et prospère…”

“…Seach by title, download your copies and start knowing more in no time: Managing Your Time Productively Developing Your Influencing Skills Delegating Effectively Managing Upwards Successfully Persuasive Communication Leading Your Team Through Change Making Effective Decisions Managing Performance and Appraisals Managing Difficult Situations and Discussions Negotiating With Confidence Writing Compelling Reports and Proposals Presenting With Confidence How to be Assertive Effective Mentoring Coaching Effectively Managing Productive Meetings Motivating Your Team Embracing Diversity Within Your Team Effective Problem Solving Interviewing With Confidence How to be a Great Leader Your first 60 days as a Leader Establish Yourself as a Leader Communicate Like a Leader Set Your Leadership priorities Lead Your Team Nurturing Business Innovation Sharpen Your Influencing Strategies How to be a Decisive Leader: Inspire Your Team to Change How to be a Successful Change Leader Making Strategic Business Change decisions Create a Successful Change Strategy How to Build Your Vision for Change Promote a Positive Change Culture How to Create an Action Plan for Change How to Communicate Change to Your Team Managing Resistance to Change Support Your Team through Change Sustaining Business Change…”

Tabla de Contenidos: “…1: Introducing Microsoft Cognitive Services -- 2: Getting Started with Computer Vision APIs -- 3: Invoking the Computer Vision APIs from C# -- 4: Computer Vision on Mobile Apps with Xamarin -- 5: Computer Vision in Web Apps with ASP.NET MVC Core…”

Tabla de Contenidos: “…4.2 Object Detection -- 4.3 Two-Stage Object Detectors -- 4.3.1 R-CNN -- 4.3.2 SPPNet -- 4.3.3 Fast RCNN -- 4.3.4 Faster RCNN -- 4.3.5 R-FCN -- 4.3.6 FPN -- 4.3.7 Mask RCNN -- 4.3.8 G-RCNN -- 4.4 One-Stage Object Detectors -- 4.4.1 YOLO -- 4.4.2 CenterNet -- 4.4.3 SSD -- 4.4.4 RetinaNet -- 4.4.5 EfficientDet -- 4.4.6 YOLOR -- 4.5 Discussion On Model Performance -- 4.5.1 Future Trends -- 4.6 Conclusion -- References -- Chapter 5 Deep Learning Algorithms for Computer Vision: A Deep Insight Into Principles and Applications -- 5.1 Introduction -- 5.2 Preliminary Concepts of Deep Learning -- 5.2.1 Artificial Neural Network -- 5.2.2 Convolution Neural Network (CNNs) -- 5.3 Recurrent Neural Network (RNNs) -- 5.4 Overview of Applied Deep Learning in Computer Vision -- 5.6 Industrial Applications of Computer Vision -- 5.7 Future Scope in Computer Vision -- 5.8 Conclusion -- References -- Chapter 6 Handwritten Equation Solver Using Convolutional Neural Network -- 6.1 Introduction -- 6.2 State-Of-The-Art -- 6.3 Convolutional Neural Network -- 6.3.1 Convolution Layer -- 6.3.2 Pooling Layer -- 6.3.3 Fully Connected Layer -- 6.3.4 Activation Function -- 6.4 Handwritten Equation Recognition -- 6.4.1 Dataset Preparation -- 6.4.2 Proposed Methodology -- 6.4.2.1 Dataset Acquisition -- 6.4.2.2 Preprocessing -- 6.4.2.3 Recognition Through CNN Model -- 6.4.2.4 Processing Inside CNN Model -- 6.4.3 Solution Approach -- 6.5 Results and Discussion -- 6.6 Conclusion and Future Scope -- References -- Chapter 7 Agriware: Crop Suggester System By Estimating the Soil Nutrient Indicators -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Proposed Methodology -- 7.4 Experimental Results and Discussion -- 7.5 Conclusion and Future Work -- References -- Chapter 8 A Machine Learning Based Expeditious Covid-19 Prediction Model Through Clinical Blood Investigations -- 8.1 Introduction…”