updated docs

docs/docs/release_notes.xml

@@ -12,41 +12,48 @@
 
 <current>
 New Features and Improvements:
-   - Made orthogonalize() faster.
-   - Added binomial_random_vars_are_different() and event_correlation().
+   - Deep Learning:
       - Added scale_ layer, allowing implementation of squeeze-and-excitation networks.
-   - Added xcorr_fft()
       - Added loss_multimulticlass_log: used for learning a collection of multi-class classifiers.
+   - Added a random forest regression tool. See random_forest_regression_trainer.
+   - Added make_bounding_box_regression_training_data()
+   - Added isotonic_regression
+   - Added momentum_filter, rect_filter, find_optimal_momentum_filter(), and
+     find_optimal_rect_filter().
+   - Added binomial_random_vars_are_different() and event_correlation().
+   - Added xcorr_fft(), a routine for efficiently performing large cross-correlations using the FFT.
    - Added the ramdump type decorator for invoking faster serialization routines.
    - Added check_serialized_version()
    - Added max_scoring_element() and min_scoring_element()
+   - Made orthogonalize() faster.
+   - Updates to the Python API:
+      - Added interface to the global_function_search object.  This is a more general
+        interface to the solver used by find_max_global().
+      - Added support for variadic Python functions in find_max_global().
+      - Added rect_filter and find_optimal_rect_filter().
       - Added make_bounding_box_regression_training_data()
-   - Added isotonic_regression.
-   - Added momentum_filter and rect_filter as well as find_optimal_momentum_filter() and find_optimal_rect_filter()
-   - Added a random forest regression tool. see random_forest_regression_trainer.
-   - Python API:
-      - Add Python rvm_trainer
-      - Added probability_that_sequence_is_increasing() to python API
-      - Made dlib.point() have writable x and y properties.
-      - Added a __time_compiled__ field to the python API.
-      - Exposed the image_dataset_metadata routines for parsing XML datasets to Python.
+      - Added the image_dataset_metadata routines for parsing XML datasets.
+      - Added rvm_trainer
+      - Added probability_that_sequence_is_increasing() 
+      - Added dlib.__time_compiled__ field
       - Added num_threads to shape_predictor_training_options.
-      - Added set_dnn_prefer_smallest_algorithms() 
-      - Added support for variadic Python functions in find_max_global.
-      - Added python interface to cuda::set_device() and other relevant functions.
-      - Added python interface to the more general global_function_search object.
+      - Added CUDA controlling routines such as set_device() and 
+        set_dnn_prefer_smallest_algorithms().
 
 Non-Backwards Compatible Changes:
-   - Changed cmake so that there is only the dlib target and it isn't forced to
-     be static or shared, instead, the build type will toggle based on the state
-     of CMake's BUILD_SHARED_LIBS variable.  So there is no longer a dlib_shared target.
-   - Change types of tensor's size-related members to prevent integer overflow.
+   - Changed CMake so that there is only the dlib target and it isn't forced to
+     be static.  Instead, the build type will toggle based on the state of CMake's
+     BUILD_SHARED_LIBS variable.  So there is no longer a dlib_shared target.
+   - Changed the integer types used to represent sizes from 32bits to 64bits in numerous
+     places, such as in the tensor object.  This should be a backwards compatible change
+     for nearly all client code.
 
 Bug fixes:
    - Fixed memory leak in java swig array binding tool.
    - Fixed windows include order problem in all/source.cpp file.
-   - Fixed cont_ layers not printing the correct num_filters parameter when they are printed to cout or xml.
-   - Fixed code not handling OBJECT_PART_NOT_PRESENT for full_object_detection objects.
+   - Fixed cont_ layers not printing the correct num_filters parameter when they were 
+     printed to std::cout or to XML.
+   - Fixed some code not handling OBJECT_PART_NOT_PRESENT values correctly.
    - Fixed fft_inplace() not compiling for compile time sized matrices.
    - The shape_predictor_trainer could have very bad runtime for some really
      bad parameter settings.  This has been fixed and also warning messages about